A business system (for example, a customer management system) implements processing of large-volume data such as big data. The big data is a collection of large-scale data, and the analysis thereof can provide information useful for the business.
When large-volume data such as big data are analyzed, a database in each system manages large volumes of data. Business systems including databases have been technologically improved to increase the processing capacity thereof. Such technological improvement is sometimes performed, for example, for each constituent element such as an application, a storage (also referred to hereinbelow as a storage device), and a network constituting the system, provided that the constituent elements to not adversely affect each other.
For example, a storage device sometimes includes a plurality of storage units that differ in a read rate, and the storage units are controlled depending on which storage unit stores data and according to the access frequency of the data. More specifically, for example, the storage device determines the access frequency to data of each type by detecting the access to the data stored in the storage device (host device). The data with a high access frequency are then stored in a storage unit with a high read rate. Alternatively, the data with a high access frequency are transferred from a storage unit with a low read rate to a storage unit with a high read rate (see, for example, Japanese Laid-open Patent Publication No. 2003-167781). Such a technique of rearranging the data between the high-speed storage unit and low-speed storage unit according to the data access frequency (referred to hereinbelow as the “automatic hierarchization technique”) increases the processing efficiency of access to the data in the storage device.